Development and validation of nomogram models for poor short-term response to recombinant human growth hormone treatment in children with short stature
10.3760/cma.j.cn311282-20241211-00583
- VernacularTitle:生长激素治疗矮小儿童短期疗效差列线图模型的开发与验证
- Author:
Xuyang GONG
1
;
Mengxing PAN
;
Qianshuai LI
;
Shuai ZHU
;
Xinjing LIU
;
Tianfang WANG
;
Xulong LI
;
Yanshuang CUI
;
Yijing XIE
;
Yi SONG
;
Linlin ZHAO
;
Jinqin WANG
;
Yawei ZHANG
;
Na XU
;
Qiao REN
;
Linqi DIAO
;
Guijun QIN
;
Yanyan ZHAO
Author Information
1. 郑州大学第一附属医院内分泌与代谢病学部，郑州 450052
- Publication Type:Journal Article
- Keywords:
Growth hormone;
Child;
Growth hormone deficiency;
Idiopathic short stature;
Treatment outcome
- From:
Chinese Journal of Endocrinology and Metabolism
2025;41(6):467-475
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.
